Phenotype Network and Brain Structural Covariance Network of Major Depression

Yun, Je Yeon; Kim, Yong Ku

doi:10.1007/978-981-33-6044-0_1

Cited by 7 publications

(9 citation statements)

References 68 publications

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“…In the analysis of group-level SCN, we did not detect any significant differences in inter-group comparisons. Despite prior investigations indicating group-level differences in structural covariance aberrance (Chen et al, 2022a;Neufeld et al, 2020;Singh et al, 2013;Watanabe et al, 2020;Xiong et al, 2021;Yun & Kim, 2021), our current study did not reveal any significant differences between patients with MDD and HCs. The inconsistent findings across studies may be attributed to factors such as small sample sizes in previous single-center investigations, comorbidities, medication, age of onset (Han et al, 2021;Schmaal et al, 2017).…”

Section: Discussioncontrasting

confidence: 99%

Altered topology of individual brain structural covariance networks in major depressive disorder

et al. 2023

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Background The neurobiological pathogenesis of major depression disorder (MDD) remains largely controversial. Previous literatures with limited sample size utilizing group-level structural covariance networks (SCN) commonly generated mixed findings regarding the topology of brain networks. Methods We analyzed T1 images from a high-powered multisite sample including 1173 patients with MDD and 1019 healthy controls (HCs). We used regional gray matter volume to construct individual SCN by utilizing a novel approach based on the interregional effect size difference. We further investigated MDD-related structural connectivity alterations using topological metrics. Results Compared to HCs, the MDD patients showed a shift toward randomization characterized by increased integration. Further subgroup analysis of patients in different stages revealed this randomization pattern was also observed in patients with recurrent MDD, while the first-episode drug naïve patients exhibited decreased segregation. Altered nodal properties in several brain regions which have a key role in both emotion regulation and executive control were also found in MDD patients compared with HCs. The abnormalities in inferior temporal gyrus were not influenced by any specific site. Moreover, antidepressants increased nodal efficiency in the anterior ventromedial prefrontal cortex. Conclusions The MDD patients at different stages exhibit distinct patterns of randomization in their brain networks, with increased integration during illness progression. These findings provide valuable insights into the disruption in structural brain networks that occurs in patients with MDD and might be useful to guide future therapeutic interventions.

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Section: Discussioncontrasting

confidence: 99%

Altered topology of individual brain structural covariance networks in major depressive disorder

et al. 2023

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“…Combing with results that identified two subtypes shared indistinguishable duration of illness, sex, age and the total HAMD score, our results revealed that high morphological heterogeneity might be inherent to the pathophysiology of depression. Although abnormal structural covariance had been reported in previous studies, they exclusively obtained group-level differential structural covariance aberrance ignoring interindividual heterogeneity (Lee et al, 2019; Neufeld & Kaczkurkin, 2020; Watanabe et al, 2020; Yun & Kim, 2021). To our knowledge, the current study was the first attempt to investigate subject-level differential structural covariance edges in depression.…”

Section: Discussionmentioning

confidence: 99%

“…Traditional case-control designs often focus on group-level aberrance while ignore the interindividual heterogeneity (Wolfers et al, 2018). Although studies have revealed altered structural covariance in depression, most of them exclusively probe group-level aberrance (Mak, Colloby, Thomas, & O'Brien, 2016; Rashidi-Ranjbar et al, 2020; Yun & Kim, 2021). Depicting individualized structural differences helps us to discover neuroimaging substrates underlying symptoms and uncover more homogeneous subtypes in heterogeneous disorders (Ajnakina et al, 2021; Das et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Resolving heterogeneity in depression using individualized structural covariance network analysis

Han

Zheng

et al. 2022

Psychol. Med.

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Background Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis. Methods T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges. Results As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms. Conclusions In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

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“…Furthermore, adults with comorbid depression are less likely to quit smoking after being diagnosed with acute coronary syndrome 36 . To date, few studies have examined the associations between health-promoting behaviors and depressive symptoms in patients with chronic disease 37 – 39 .…”

Section: Introductionmentioning

confidence: 99%

Health-promoting behavior to enhance perceived meaning and control of life in chronic disease patients with role limitations and depressive symptoms: a network approach

Yun

2023

Sci Rep

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The association between health-related role limitations in the mental and physical subdomains and clinical status (i.e., chronic disease and comorbid depressive symptoms) is mediated by health-promoting behaviors. To enhance health-promoting behaviors in adults with chronic disease, it is necessary to identify item-level associations among targets of health-related monitoring and management. Therefore, the current study used a network approach to examine associations among health-related role limitations, depressive symptoms, existential well-being, socioeconomic position, and health-promoting behavior in adults with chronic disease. A total of 535 adults (mean ± SD age = 62.9 ± 11.9 years; males, n = 231, females, n = 304) who were regularly visiting an outpatient clinic for chronic disease treatment participated in this cross-sectional study. Data on participant demographics, chronic disease diagnoses, socioeconomic status, health-related role limitations (12-item short form survey scores), depressive symptoms (patient health questionnaire-9 scores), existential well-being (scores for four items of the McGill quality of life questionnaire-Revised), and health-promoting behavior (Healthy Habits Questionnaire scores) were acquired. “Undirected regularized partial correlations” and “directional joint probability distributions” among these variables were calculated using a mixed graphical model (MGM) and directed acyclic graph (DAG). In the MGM, the most influential nodes were emotional well-being, feelings of failure, and health-related limitations affecting usual role and physical activities. According to both the MGM and DAG, the relationship between emotional well-being and feelings of failure mediated the relationships of health-related role limitations with concentration difficulty and suicidal ideation. A positive mindset was dependent on the probability distributions of suicidal ideation, controllability of life, and positive self-image. Both the meaning of life and a positive mindset had direct associations with proactive living. Specifically, proactive living was associated with a balanced diet, regular exercise, volunteering in the community, and nurturing intimacy in social interactions. The meaning and controllability of life in individuals with chronic diseases could mediate the relationships of health-promoting behavior with health-related limitations related to usual role activities, physical activities, and depressive symptoms. Thus, interventions targeting health-promoting behaviors should aim to enhance the meaning and controllability of life (as it pertains to limitations in usual role and physical activities), as well as promote proactive screening and timely psychiatric treatment of depressive symptoms including feelings of failure, concentration difficulties, and suicidal ideation.

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Phenotype Network and Brain Structural Covariance Network of Major Depression

Cited by 7 publications

References 68 publications

Altered topology of individual brain structural covariance networks in major depressive disorder

Altered topology of individual brain structural covariance networks in major depressive disorder

Resolving heterogeneity in depression using individualized structural covariance network analysis

Health-promoting behavior to enhance perceived meaning and control of life in chronic disease patients with role limitations and depressive symptoms: a network approach

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